@article {McCann6,
author = {McCann, Craig and Qin, Chuan and Yan, Mike},
title = {How Widespread and Predictable Is Stock Broker Misconduct?},
volume = {26},
number = {2},
pages = {6--25},
year = {2017},
doi = {10.3905/joi.2017.26.2.006},
publisher = {Institutional Investor Journals Umbrella},
abstract = {We reconcile widely diverging recent estimates of broker misconduct. Qureshi and Sokobin [2015] reported that 1.3\% of a sample of current and former brokers was associated with awards or settlements in excess of a threshold amount. Egan, Matvos, and Seru [2016] found that 7.8\% of all current and former brokers have financial misconduct disclosures, including customer complaints, awards, and settlements. Applying Qureshi and Sokobin{\textquoteright}s restrictive definition of potential misconduct to all brokers, we find that 2.3\% of all current and former brokers have been associated with awards or settlements in excess of a threshold amount.Qureshi and Sokobin found that the top quintile of brokers sorted by estimated likelihood of being the subject of a customer complaint contains 55\% of the brokers subsequently subject to complaints. We demonstrate that more sophisticated data mining techniques can sort brokers so that the highest risk quintile contains 75\% of the brokers subsequently subject to customer complaints.We evaluate Qureshi and Sokobin{\textquoteright}s claim that BrokerCheck provides helpful information to investors seeking to avoid bad brokers and answer the question posed by Egan, Matvos, and Seru: If BrokerCheck data can predict broker misconduct, why do investors not use those data to protect themselves? We find that BrokerCheck is nearly worthless in its current form but could easily be modified so that investors could protect themselves and market forces would substantially reduce broker misconduct.},
issn = {1068-0896},
URL = {https://joi.iijournals.com/content/26/2/6},
eprint = {https://joi.iijournals.com/content/26/2/6.full.pdf},
journal = {The Journal of Investing}
}